Genetics of female interspecific mate rejection in species of Drosophila

Speciation can occur when accumulated differences in mating behavior force diverging species to remain reproductively isolated from one another. A key determinant of behavioural isolation is the evolution of female mating preferences that prevent interspecific males from mating. However, no individual genes involved in species-specific preferences of females have yet been identified. Using various genetic mapping techniques available for studying strains and species of Drosophila, I identify candidate genes involved in D. simulans female discrimination against D. melanogaster males. One candidate gene in particular, Katanin-60, was selected for further characterization. Katanin-60 is a gene encoding a microtubule severing protein that has been previously implicated in Drosophila behaviour. Transgenic rescue of Katanin-60 expression using the GAL4/UAS system revealed the potential involvement of specific neural lobes of the Mushroom bodies in interspecific discrimination. Further characterization of the behaviour through modifying male mating signals showed that the type-aversive cue females are discriminating against is found in male wing song. However, this was not true of all strains and species tested, indicating that many means of mate assessment have diversified within the genus. One other species, D. sechellia, was additionally mapped for their females’ discrimination against D. simulans males. Quantitative trait locus mapping identified two loci for interspecific preference that were then compared to other maps of interspecific divergence between the two species

Strong Purifying Selection at Synonymous Sites in D. melanogaster

Synonymous sites are generally assumed to be subject to weak selective constraint. For this reason, they are often neglected as a possible source of important functional variation. We use site frequency spectra from deep population sequencing data to show that, contrary to this expectation, 22% of four-fold synonymous (4D) sites in D. melanogaster evolve under very strong selective constraint while few, if any, appear to be under weak constraint. Linking polymorphism with divergence data, we further find that the fraction of synonymous sites exposed to strong purifying selection is higher for those positions that show slower evolution on the Drosophila phylogeny. The function underlying the inferred strong constraint appears to be separate from splicing enhancers, nucleosome positioning, and the translational optimization generating canonical codon bias. The fraction of synonymous sites under strong constraint within a gene correlates well with gene expression, particularly in the mid-late embryo, pupae, and adult developmental stages. Genes enriched in strongly constrained synonymous sites tend to be particularly functionally important and are often involved in key developmental pathways. Given that the observed widespread constraint acting on synonymous sites is likely not limited to Drosophila, the role of synonymous sites in genetic disease and adaptation should be reevaluated

A new effective method for estimating missing values\ud in the sequence data prior to phylogenetic analysis

In this article we address the problem of phylogenetic inference from nucleic acid data containing missing bases. We introduce a new effective approach, called “Probabilistic estimation of missing values” (PEMV), allowing one to estimate unknown nucleotides prior to computing the evolutionary distances between them. We show that the new method improves the accuracy of phylogenetic inference compared to the existing methods “Ignoring Missing Sites” (IMS), “Proportional Distribution of Missing and Ambiguous Bases” (PDMAB) included in the PAUP software [26]. The proposed strategy for estimating missing nucleotides is based on probabilistic formulae developed in the framework of the Jukes-Cantor [10] and Kimura 2-parameter [11] models. The relative performances of the new method were assessed through simulations carried out with the SeqGen program [20], for data generation, and the BioNJ method [7], for inferring phylogenies. We also compared the new method to the DNAML program [5] and “Matrix Representation using Parsimony” (MRP) [13], [19] considering an example of 66 eutherian mammals originally analyzed in [17]

Receptor uptake arrays for vitamin B12, siderophores and glycans shape bacterial communities

Molecular variants of vitamin B12, siderophores and glycans occur. To take up variant forms, bacteria may express an array of receptors. The gut microbe Bacteroides thetaiotaomicron has three different receptors to take up variants of vitamin B12 and 88 receptors to take up various glycans. The design of receptor arrays reflects key processes that shape cellular evolution. Competition may focus each species on a subset of the available nutrient diversity. Some gut bacteria can take up only a narrow range of carbohydrates, whereas species such as B.~thetaiotaomicron can digest many different complex glycans. Comparison of different nutrients, habitats, and genomes provide opportunity to test hypotheses about the breadth of receptor arrays. Another important process concerns fluctuations in nutrient availability. Such fluctuations enhance the value of cellular sensors, which gain information about environmental availability and adjust receptor deployment. Bacteria often adjust receptor expression in response to fluctuations of particular carbohydrate food sources. Some species may adjust expression of uptake receptors for specific siderophores. How do cells use sensor information to control the response to fluctuations? That question about regulatory wiring relates to problems that arise in control theory and artificial intelligence. Control theory clarifies how to analyze environmental fluctuations in relation to the design of sensors and response systems. Recent advances in deep learning studies of artificial intelligence focus on the architecture of regulatory wiring and the ways in which complex control networks represent and classify environmental states. I emphasize the similar design problems that arise in cellular evolution, control theory, and artificial intelligence. I connect those broad concepts to testable hypotheses for bacterial uptake of B12, siderophores and glycans.Comment: Added many new references, edited throughou

Alignment and Prediction of cis-Regulatory Modules Based on a Probabilistic Model of Evolution

Cross-species comparison has emerged as a powerful paradigm for predicting cis-regulatory modules (CRMs) and understanding their evolution. The comparison requires reliable sequence alignment, which remains a challenging task for less conserved noncoding sequences. Furthermore, the existing models of DNA sequence evolution generally do not explicitly treat the special properties of CRM sequences. To address these limitations, we propose a model of CRM evolution that captures different modes of evolution of functional transcription factor binding sites (TFBSs) and the background sequences. A particularly novel aspect of our work is a probabilistic model of gains and losses of TFBSs, a process being recognized as an important part of regulatory sequence evolution. We present a computational framework that uses this model to solve the problems of CRM alignment and prediction. Our alignment method is similar to existing methods of statistical alignment but uses the conserved binding sites to improve alignment. Our CRM prediction method deals with the inherent uncertainties of binding site annotations and sequence alignment in a probabilistic framework. In simulated as well as real data, we demonstrate that our program is able to improve both alignment and prediction of CRM sequences over several state-of-the-art methods. Finally, we used alignments produced by our program to study binding site conservation in genome-wide binding data of key transcription factors in the Drosophila blastoderm, with two intriguing results: (i) the factor-bound sequences are under strong evolutionary constraints even if their neighboring genes are not expressed in the blastoderm and (ii) binding sites in distal bound sequences (relative to transcription start sites) tend to be more conserved than those in proximal regions. Our approach is implemented as software, EMMA (Evolutionary Model-based cis-regulatory Module Analysis), ready to be applied in a broad biological context

The evolution of immune genes in tsetse flies (Glossina) and insights into tsetse-symbiont-trypanosome interactions

Tsetse flies (genera Glossina) are the sole biological vectors of African Trypanosoma species, the infectious agents of African Trypanosomiasis. Vector control is a key inhibitor of disease transmission; however, long-term control measures are economically and ecologically unsustainable and therefore, alternatives must be explored. In this thesis we aim to explore the evolution of three important immune genes: attacin-A (AttA), Defensin (Def) and Toll-like receptor 2 (TLR2), in relation to symbionts and parasitic interactions. This could in turn lay the foundations for genetic control methods The successful identification of novel attacin orthologues confirmed the previous descriptions of attacin clusters within the Glossina genome, while a single novel defensin orthologue was identified in each of the six Glossina genomes. A total of six TLRs were confirmed within the Glossina genome, and three additional TLRs were potentially identified, though these are unconfirmed. The evolutionary history of the attacin cluster remains undetermined, however concerted evolution likely impacts the evolution of AttA, while Def and TLRs are governed by strict Darwinian selection. A wild population sample of Glossina morsitans morsitans illustrated differing levels of nucleotide variation in each gene, Def being the least polymorphic (n = 8) and TLR2 being the most (n = 22). All genes indicated a recent population expansion event and deviations from neutrality, indicative of population expansion and balancing selection. Genetic variation in both AttA and TLR2 was found to be maintained via purifying selection, while Def exhibited signs of the Red Queen arms race and balancing section. Trypanosome infection rates were unexpectedly high (69.35%), consisting of mixed species infections. Advantageous Def variants were observed to reduce infection rates within samples, while an observable relationship between TLR2 and symbiont variation, and infection rate requires further research. The results within described the impacts of evolution and population change on immune genes and how the interactions with symbiont populations can influence trypanosome infection rates. This thesis indicates that an understanding of the evolution and interactions of the tsetse-symbiont-trypanosome triplet could be used to inform novel genetic control methods

Resursdynamik hos humlor : en genomgång av födo- och boplatsresurser i det agrara landskapet

90 % of all plants on earth either benefits or entirely depends on pollination. There are pollinators among families of bees (Apidea), butterflies (Lepidoptera) and birds (Aves). Bees of genus Bombus spp., bumblebees, are especially important and provide pollination service for 80 % of the crops of Europe and many wild plant species. The bumblebee community both rise and fall within the same year with few exceptions. Only the newborn queen survives to the next year to form a new community. Since the intensification of agriculture many bumblebees species have been declining in numbers. The purpose of this thesis was to review the drivers of bumblebees in the agricultural landscape, focusing on nesting and foraging. The aim was to understand what controls the quantity of bumblebees, which species were to be found and why them. This thesis consists of two parts: one reviewing foraging and nesting by a literature review and the other a field study of the effects of flower strips and honeybees. In the field study, I searched for bumblebee queens emerging in spring the year after an experiment with honeybees (Apis mellifera) and flower strips in fava beans (Vicia faba). I could not find a significant effect of flower strips nor honeybees in my field study. However, in my review several researches have come to the conclusion that both honeybees and flower strips can affect bumblebee density and thereby also potentially bumblebee dynamics. For instance, the impact of honeybees could be minimized by keeping the hives within the ecosystem the year around and not within areas with sensitive or endangered plant or bee species. Flower strips could potentially positively affect bumblebee population dynamics if the timing and floral quality meets the temporal need of the bumblebee populations, especially during critical events such as nest establishment and queen reproduction. We need further testing of the impact of floral abundance in the agricultural landscape and presence of honeybees on bumblebee population dynamics, mainly during critical events such as nest establishment. Because this field study was first of its kind in Sweden, the method needs to be refined to better handle the impact of timing and changes in weather. Therefore several more studies during nest establishment are needed, studying the impact of overwintering survival and fitness of queens